By Ted Stone, Insight Sales Director, Reward
You’ve seen it before: an ad for something you already bought, a promotion for a brand you barely remember, a message based on who you were weeks ago – not who you are today.
The targeting looks right on paper, based on your age, your postcode, your income bracket, but relevance has moved on. The ad hasn’t.
And that distinction matters more than ever. At a time when AI has made personalisation faster, cheaper, and infinitely more scalable, consumers are still immersed with marketing that feels mis-timed, generic or disconnected from what they actually care about. Creative production that once took weeks now takes hours. Media activation is increasingly automated. Audience segmentation has become hyper-granular.
Yet much of the output still feels like guesswork.
Because while personalisation has become easy, relevance remains hard.
The Missing Ingredient Isn’t Technology. It’s Quality Data.
Most targeting today still relies heavily on audience assumptions.
Demographic indicators. Inferred interests. Lookalike models stitched together from fragmented third-party signals. These attributes can help describe who someone appears to be. But they say very little about what they’re actually doing.
- Where are they spending right now?
- What habits are they changing?
- Which brands are they switching to?
That’s the blind spot.
And the gap is growing. Privacy regulation has reshaped the ecosystem. Third-party cookies are disappearing. Consent frameworks are tighter.
Consumers aren’t just asking for transparency and control over their data. They expect value in exchange for it, delivered through the right offer, at the right time, in the right context.
That’s a positive shift. But it also means the value of privacy-safe, purchase-based data has increased dramatically.
Research published in the Journal of Advertising Research in 2025, a meta-analysis spanning 53 experimental studies, found that perceived relevance, not personalisation mechanics, is what drives advertising effectiveness. Poorly targeted or intrusive ads actively reduced performance.
In other words: the fuel matters more than the engine.
Relevance isn’t a creative problem. It isn’t an automation problem. It’s a data problem.
You Know Less About Your Customer Than You Think
Take Mike.
He’s 38, lives in Manchester, married with two children and works in financial services. On paper, that gives marketers plenty to work with. He fits neatly into multiple audience segments: premium grocery shopper, urban professional, weekend family leisure seeker.
But those attributes only tell part of the story.
What they don’t reveal is that Mike recently shifted his weekly grocery spend to a competitor. Or that he’s started spending heavily at DIY home improvement stores. Meanwhile, the brand trying to retain him continues serving the same loyalty messaging it’s been using for months, completely unaware his behaviour has already changed.
The targeting still “works” in a technical sense. The creative may even be strong. But the message is no longer relevant.
That’s the difference between personalisation and relevance: one is about how a message is delivered; the other is about whether it reflects where a customer actually is right now.
Moving Beyond Assumptions to Transactional Truth
This is where RewardIQ changes the equation.
RewardIQ is built on real transaction data, billions of verified purchase signals from more than 5 million UK cardholders across 3,500+ brands. Not inferred behaviour. Not modelled intent. Actual spend.
Through a privacy-safe clean room environment, brands can securely connect first-party data with real-world consumer behaviour to understand not just who customers are, but what they’re actually doing beyond your four walls.
That changes what’s possible.
Identify high-value audiences through real spend behaviour
Instead of relying on predicted affinity, brands can identify consumers based on demonstrated purchasing behaviour, like who is already spending in-category, increasing share of wallet, or showing signals associated with long-term value.
Customer acquisition grounded in evidence, not assumption.
Detect market shifts while they’re happening
Consumer behaviour doesn’t wait for quarterly reporting cycles. With access to live transactional insight, brands can spot competitive movement and category shifts as they emerge, whether customers are migrating to competitors, reducing frequency or changing spending patterns altogether.
That means brands can respond while there’s still time to influence outcomes.
Activate insight across paid and owned channels
Data only creates value when it drives action. RewardIQ provides a 360-degree view of the customer, grounded in real-world spending behaviour, not just who consumers are, but how they spend and what they value. The result is marketing that performs more efficiently because it aligns with how people actually spend.
The Next Evolution of Marketing Isn’t More Automation
AI has democratised personalisation mechanics.
Anyone can now generate dynamic creative, automate segmentation, and optimise delivery at scale. But increasing the sophistication of delivery doesn’t solve the underlying challenge if the data itself lacks behavioural depth. Layering more automation onto the same old proxies won’t change that.
The real competitive advantage now lies in understanding consumers closely enough to engage them with messages that genuinely reflect their current buying behaviour, priorities, and intent.
Research into data-driven personalisation in e-commerce continues to reinforce the same conclusion: commercial performance depends less on the existence of personalisation and more on the quality of customer understanding behind it.
The next evolution of performance marketing is better matching. Better signals. Better understanding.
Relevance that’s grounded in real purchase behaviour. That’s a harder problem to solve than personalisation. It’s also a far more valuable one.
And it’s exactly what RewardIQ is built for.
Sources: “How Persuasive Is Personalized Advertising? A Meta-Analytic Review,” Journal of Advertising Research (April 2025); Springer, “Exploring the Effectiveness of Personalized Marketing Strategies in E-commerce” (2025).
